Struct FittedMultiOutputLinearRegression 

pub struct FittedMultiOutputLinearRegression<F> { /* private fields */ }

Fitted multi-output ordinary least squares linear regression model.

The 2-D-target companion to FittedLinearRegression: produced by Fit<Array2<F>, Array2<F>> when fitting a 2-D Y of shape (n_samples, n_targets). Mirrors scikit-learn’s multi-output LinearRegression (MultiOutputMixin, _base.py:465), whose coef_ is a 2-D array of shape (n_targets, n_features) and intercept_ an array of shape (n_targets,) (_base.py:499/:511). Stored in sklearn’s coef_ orientation (target rows), so coefficients() maps directly onto sklearn.coef_.

Implementations

impl<F: Float> FittedMultiOutputLinearRegression<F>

pub fn coefficients(&self) -> &Array2<F>

Learned coefficient matrix, shape (n_targets, n_features) (sklearn coef_, _base.py:499).

pub fn intercepts(&self) -> &Array1<F>

Learned per-target intercepts, shape (n_targets,) (sklearn intercept_, _base.py:511).

pub fn rank(&self) -> usize

Effective rank of the design matrix (sklearn rank_, _base.py:505).

pub fn singular_values(&self) -> &Array1<F>

Singular values of the design matrix (sklearn singular_, _base.py:508).

Trait Implementations

impl<F: Clone> Clone for FittedMultiOutputLinearRegression<F>

fn clone(&self) -> FittedMultiOutputLinearRegression<F>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<F: Debug> Debug for FittedMultiOutputLinearRegression<F>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<F: Float + Send + Sync + ScalarOperand + 'static> Predict<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for FittedMultiOutputLinearRegression<F>

fn predict(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Predict 2-D target values for the given feature matrix.

Computes X @ coefficients.T + intercepts (broadcasting the per-target intercepts over rows), shape (n_samples, n_targets), mirroring sklearn’s 2-D _decision_function arm X @ coef_.T + self.intercept_ (_base.py:290).

Errors

Returns FerroError::ShapeMismatch if the number of features does not match the fitted model.

type Output = ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>

The prediction output type (e.g., ndarray::Array1<F> or ndarray::Array1<usize>).

type Error = FerroError

The error type returned by predict.